Assessing driver ability to operate an autonomous vehicle

ABSTRACT

A computer-implemented method of assessing driver capability for operating an autonomous vehicle includes identifying a human operator of the autonomous vehicle, the human operator being associated with a driving capability profile. The method further includes signaling to the human operator with the signal, the signal requesting a response from the human operator. The method also includes updating, based on the response from the human operator to the signal, the driving capability profile to indicate a level of skill of the human operator at responding to the signal.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.16/806,708, filed Mar. 2, 2020, which is a continuation of U.S. patentapplication Ser. No. 15/957,723, filed Apr. 19, 2018, which are herebyincorporated by reference in their entirety.

BACKGROUND

Vehicles may be equipped with sensors for processing and communicationcapabilities that allow the vehicle to navigate autonomously withouthuman intervention. Autonomous vehicle navigation is not possible,however, under all circumstances. In some situations, a vehicle may lackthe capability to navigate autonomously such as adverse or extremeweather conditions, in the event of the loss of vehicle sensors or acommunications link, under disaster conditions, due to vehiclecollisions in the area, etc. When a vehicle can no longer navigateautonomously, control of the vehicle may be returned to a humanoperator. Transfer of control of the vehicle to a human represents apotential danger due to the vehicle's autonomous nature—a human operatorwho has been traveling in the vehicle may be inattentive to roadconditions and unprepared to make the decisions and exercise the motorcontrol needed to safely operate the vehicle. Human operators willdiffer in their ability to operator an autonomous vehicle, especiallywhen accepting increased driving responsibilities, and therefore presentvarying levels of risk in operating autonomous vehicles.

SUMMARY OF THE DISCLOSURE

This summary is provided to introduce a selection of concepts in asimplified form that are further described in the Detailed Descriptions.This summary is not intended to identify key features or essentialfeatures of the claimed subject matter, nor is it intended to be used tolimit the scope of the claimed subject matter.

Systems and methods are disclosed for assessing driver capability foroperating an autonomous vehicle. Human operators of autonomous vehiclesmay exhibit varying levels of operating proficiencies and may responddifferently to changing road conditions or requests from the vehicle toassume more or less control over navigation. A system for assessingdriver capability of an autonomous vehicle assesses human operatorcapabilities in a variety of circumstances to assemble a drivingcapability profile of the human operator. The autonomous vehicle mayrely on the driving capability profile as well as an environmentalprofile and human operator parameters describing the environmentsurrounding the vehicle and an alertness level of the human operator,respectively. The vehicle may condition requests to increase or decreasedriving responsibilities of the human operator depending on the drivingcapability profile in combination with the environmental profile and/orthe human operator parameters. An insurer may condition an insurancepremium cost for a time period based on the driving capability profilein combination with the environmental profile and/or the human operatorparameters.

In one aspect, a method is disclosed for assessing driver capability foroperating an autonomous vehicle. The method may include identifying ahuman operator of the autonomous vehicle, the human operator beingassociated with a driving capability profile; signaling to the humanoperator with a signal requesting a response from the human operator;and updating the driving capability profile based on the response fromthe human operator to indicate a level of skill of the human operator atresponding to the signal.

In another aspect, a computer system is provided for assessing drivercapability for operating an autonomous vehicle. The system may includeone or more processors and a non-transitory computer-readable memorycoupled to the one or more processors and storing instructions thereon.When executed by the one or more processors, the instructions cause thecomputer system to: identify a human operator of the autonomous vehicle,the human operator being associated with a driving capability profile;signal to the human operator with a signal, the signal requesting aresponse from the human operator; and update, based on the response fromthe human operator to the signal, the driving capability profile toindicate a level of skill of the human operator at responding to thesignal.

In yet another aspect, a method of insuring an autonomous vehicleagainst loss is disclosed. The method may include: receiving, by one ormore processors, a driving capability profile of a human operator of theautonomous vehicle; receiving a response from the human operator to asignal, the signal presented to the human operator and requesting aresponse from the human operator; updating, based on the response fromthe human operator to the signal, the driving capability profile toindicate a level of skill of the human operator at responding to thesignal; determining a risk of insuring the autonomous vehicle, the riskbeing based at least in part on the updated driving capability profile;and transmitting an insurance offer to an electronic device associatedwith the human operator, the insurance offer being based at least inpart on the determined risk of insuring the autonomous vehicle.

The methods may be implemented via computer systems, and may includeadditional, less, or alternate actions or functionality. Systems orcomputer-readable media storing instructions for implementing all orpart of the method described above may also be provided in some aspects.Systems for implementing such methods may include one or more of thefollowing: a special-purpose computing device, a personal electronicdevice, a mobile device, a wearable device, a processing unit of avehicle, a remote server, one or more sensors, one or more communicationmodules configured to communicate wirelessly via radio links, radiofrequency links, and/or wireless communication channels, and/or one ormore program memories coupled to one or more processors of the personalelectronic device, processing unit of the vehicle, or remote server.Such program memories may store instructions to cause the one or moreprocessors to implement part or all of the method described above.Additional or alternative features described herein below may beincluded in some aspects.

This summary is provided to introduce a selection of concepts in asimplified form that are further described in the Detailed Descriptions.This summary is not intended to identify key features or essentialfeatures of the claimed subject matter, nor is it intended to be used tolimit the scope of the claimed subject matter.

Advantages will become more apparent to those of ordinary skill in theart from the following description of the preferred aspects, which havebeen shown and described by way of illustration. As will be realized,the present aspects may be capable of other and different aspects, andtheir details are capable of modification in various respects.Accordingly, the drawings and description are to be regarded asillustrative in nature and not as restrictive.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a schematic diagram of an example system for assessing driverability to operate an autonomous vehicle.

FIG. 2 is a time-series schematic diagram of an example system forassessing driver ability to operate an autonomous vehicle.

FIG. 3 is a plot of likelihood of loss against driving capabilityprofile in an example system for accessing driver ability to operate anautonomous vehicle.

FIG. 4 is a schematic diagram of road hazards on a road carryingautonomously navigated vehicles.

FIG. 5 is an in-vehicle view of an example system for assessing driverability to react to road conditions and/or accept additional drivingresponsibilities.

FIG. 6 is an in-vehicle view of an example system for assessing driverability to react to road conditions and/or accept additional drivingresponsibilities.

FIG. 7 is an in-vehicle view of an example system for assessing driverability to react to road conditions and/or accept additional drivingresponsibilities.

FIG. 8 is a schematic diagram of an example system for assessing driverability to operate an autonomous vehicle.

FIG. 9 is a schematic diagram of an example system for assessing driverability to operate an autonomous vehicle.

FIG. 10 is an in-vehicle view of an example system for assessing driverability to react to road conditions and/or accept additional drivingresponsibilities.

FIG. 11 is an in-vehicle view of an example system for assessing driverability to react to road conditions and/or accept additional drivingresponsibilities.

FIG. 12 is an in-vehicle view of an example system for assessing driverability to react to road conditions and/or accept additional drivingresponsibilities.

FIG. 13 illustrates example operations for assessing driver ability tooperate an autonomous vehicle.

FIG. 14 illustrates example operations assessing driver ability tooperate an autonomous vehicle.

DETAILED DESCRIPTIONS

Autonomous vehicles may exercise a range of capabilities when navigatingon open road conditions. An autonomous vehicle need not be viewed asoperating purely autonomously or purely manually. The Society ofAutomotive Engineers (SAE) has identified at least six levels ofautonomous vehicle capability ranging from no driving automation (Level0) to full automation (Level 5). As a vehicle moves up the levels ofcapability, additional autonomous competencies are added to thevehicle's set of skills (e.g., adaptive cruise control, parking assist,lane assist, traffic jam assist, conditional automation, highautomation, full automation, etc.).

At the various points on the vehicle's autonomous capability ladder, ahuman operator exercises an appropriate level of manual control. If avehicle supplies only adaptive cruise control or parking assistcapabilities, then the human operator must exercise a high level ofmanual control and is responsible for any and all non-autonomous aspectsof the vehicle. If a vehicle supplies high or full automation, on theother hand, a human operator may participate at a low level, or even notat all, in navigating the vehicle. If a vehicle exercises a high levelof autonomous capability (e.g., Levels 4 or 5), a human operator maybecome disengaged from the road and unaware of the road environmentsurrounding the vehicle. The human user may become focused onnon-driving tasks (e.g., reading, working, playing games, conversationswith other passengers, phone calls, etc.). A human operator may even goto sleep and lose all contact with controlling the vehicle.

It may be desirable for an autonomous vehicle to shift from one level ofautonomous capability to another, such as due to changing roadconditions, weather conditions, due to a vehicle crash, disaster oremergency situation, etc. To the extent the human operator will need tochange her involvement in piloting the vehicle when the vehicle shiftsbetween levels of automation, she must be notified of the impendingchange. A variety of notification types are used in the system formanual control re-engagement to communicate with the human operatorregarding upcoming changes in the human operator's responsibilities inpiloting the vehicle. A notification may be more intrusive to the humanoperator or less intrusive to the human operator depending on theurgency of the impending change to the vehicle's capabilities and thehuman operator's responsibilities.

Different human operators will respond differently to notifications ofchanges to the vehicle's autonomous capabilities. Human operatorsexhibit differences from one another in terms of attention span, abilityto multitask, ability to shift focus from one activity to another afterreceiving a notification, etc. To some extent, these differences arenatural characteristics of the human operators themselves (e.g., somepeople are more likely than others to become engrossed in reading a bookand may take more time to respond to a notification of impending vehicleautonomous capability change than other people who may tend not tobecome engrossed in reading a book while riding in a car). In othersituations, a human operator's ability to acknowledge a notification andprepare to exercise more or less control over the vehicle may depend onother aspects of the human operator that may change over time (e.g.,intoxication level, how well rested the human operator is, whether thehuman operator has become focused on another activity or remains awareof the vehicle's surroundings, the health of the human operator, etc.).In yet other situations, a human operator's ability to acknowledge anotification and prepare to exercise more or less control over thevehicle may change slowly over time (e.g., a human operator's eyesightmay deteriorate over time, motor control deteriorates with age, etc.).

A change to a vehicle's autonomous capability may also have a variabletime target in which the change should be made. Some changes to avehicle's autonomous capabilities must be made quickly, such as inemergency situations (e.g., a vehicle crash or other rapidly approachingroad hazard, if the human operator experiences an emergent medical orhealth problem, etc.). Other changes to a vehicle's autonomouscapabilities need not be made quickly (e.g., if adverse or extremeweather conditions are forecasted but not yet experienced, if a humanoperator is nearing the limits of her ability to stay awake, if a humanoperator experiences abnormal but not threatening health issues, etc.).

A vehicle may receive an indication from third-party sources of animpending road hazard and may determine the urgency of altering thevehicle's autonomous capabilities on its own. Vehicles may communicatewirelessly with one another to relay updates to one another regardingchanging road conditions as experienced by the vehicles themselves. Thevehicles may communicate according to a peer-to-peer network in whichthe vehicles connect with one another directly (e.g., a swarm) or acentralized party may collect information from the vehicles, optionallyprocess the information, and selectively provide relevant information tovehicles as the vehicles need it (e.g., client/server). For example, ifa vehicle crash occurs on a road and vehicles in the vicinity detect thecrash occurrence, the vehicle in the vicinity of the crash maycommunicate an emergency signal to vehicles approaching the crash siteon the road such that those vehicles may take precautions to avoidcrashing into any vehicles that are slow, stopped, or otherwisenavigating differently than expected due to the crash.

In another implementation, a vehicle may receive an indication from athird-party that the vehicle should alter its autonomous capabilitiesand may receive a target time period in which to make the changetherewith. A centralized authority (e.g., a weather prediction bureau,an insurer, a vehicle owner, a government agency, etc.) may determinethat a change should be made to a vehicle's autonomous capabilitiesbased on information regarding the vehicle's environment and maycommunicate a request to make the change to the vehicle. Such a requestmay accompany a target time in which to make the change to the vehicle'scapabilities.

A vehicle may adjust its autonomous capabilities to increase or decreasethe number of autonomous capabilities, depending on the situation thevehicle is in. In some situations, the vehicle may be ill-suited tosafely navigate a situation autonomously, and manual control may bepreferable (e.g., navigation in close quarters with other vehicleswherein human communication is needed to coordinate with the operatorsof other vehicles, if the vehicle experiences a sensor or other hardwarefailure, if the vehicle loses a communications link, etc.). In othersituations, a human operator may be more ill-suited to safely navigate asituation than the vehicle would be autonomously. It may be known thathuman operators in general, or a specific human operator, is likely tomake a mistake that could lead to a crash that an autonomouslycontrolled vehicle would not make. For example, if a vehicle istraveling at a high rate of speed in low visibility conditions (e.g.,heavy fog, frequent road elevation changes, blind spots, etc.) and isapproaching a sudden traffic jam wherein other vehicles are traveling ata comparatively much slower rate of speed or are stopped on a road, itmay be known that human operators are less likely to reduce speed intime than an autonomous vehicle would be. If the vehicle detects such aroad condition approaching, it may request the human operator relinquishsome or all control of the vehicle to reduce risk of a vehicle crash.

Human operators may be assessed to determine a level of capability foroperating an autonomous vehicle is possessed by the human operator. Alevel of capability may include more than a scalar value representingthe human operator's overall capability. Instead, the capability of ahuman operator in operating an autonomous vehicle may be represented bya driving capability profile that integrates information from a varietyof sources and may evaluate the human operator in a variety ofconditions. For example, some human operators may be more adept atoperating the autonomous vehicle in adverse weather conditions (e.g.,night driving, snow, rain, heavy winds, etc.) than other humanoperators. A driving capability profile may evaluate other aspects of ahuman operator as well. Some human operators may be more inclined tofocus their attention on objects other than the environment surroundingthe vehicle, such as on a book, electronic device, daydreaming, etc.Such a human operator may require more time to acclimate to increaseddriving responsibilities, should she be called on to exercise them. Adriving capability profile may take into account human operatorparameters, which are variable parameters regarding the human operatorthat may be detected by the vehicle or inferred from other information(e.g., driving history, driving habits, etc.). Human operator parametersmay include the human operator's body position, aspects of the humanoperator's body (e.g., heart rate, body temperature, eye movements,etc.) that have a bearing on the human operator's autonomous vehicleoperating capabilities. For example, a human operator who normallyresponds quickly to requests for increased driving responsibility maynot respond quickly if current human operator parameters indicate thatshe is drowsy.

FIG. 1 is a schematic diagram of an example system 100 for assessingdriver ability to operate an autonomous vehicle. The system 100 assessesa human operator 102 of a vehicle 104 in a variety of manners toassemble a driving capability profile for the human operator 102. In oneimplementation, a controlled driver capability assessment 106 maycollect driving capability profile information regarding the humanoperator 102. A controller driver capability assessment 106 may includea classroom examination of the human operator 102 (e.g., testingknowledge of rules of the road, vehicle operation, etc.) as well ascontrolled driving conditions (e.g., closed track). A human operator maybe evaluated in controlled driving conditions by observers and/orinformation regarding the human operator's performance may be collectedelectronically.

In another implementation, the system 100 assesses the human operator102 in real-world driving conditions 108. Real world driving conditions108 are likely to capture a wider variety of conditions than controlleddriver assessment 106 and are likely to capture driving behavior thatthe human operator 102 may be unlikely to engage in while she knows sheis under supervision (e.g., bad driving habits, excessive risk taking,etc.). The vehicle 104 may collect human operator parameters regardingthe human operator 102. The human operator parameters collected inreal-world driver capability assessment 108 may also include non-visualdata collected from the interior of the vehicle 102. In at least oneimplementation, non-visual data includes biometric data of the humanoperator (e.g., heart rate, breathing rate, body temperature,perspiration rate, etc.). Biometric data may be collected via the seatin the vehicle 104 because the seat is in physical contact with thehuman operator 102, which facilitates the collection of various types ofbiometric data. For example, a sensor may be embedded in the seat suchthat the sensor can collect relevant data (e.g., a thermometer, a heartrate sensor, a breathing rate sensor, a perspiration sensor, etc.). Adriver capability profile for human operator 102 may be updated withinformation gleaned from the real-world driver capability assessment 108to reflect the propensity of a particular human operator to respondeffectively to the various road conditions encountered when the humanoperator is in the various measured states of alertness.

Another aspect of the driving capability profile of the human operator102 is a vehicle capability assessment 108. Vehicles may differ invarious ways that affect the ability of the vehicle to avoid roadhazards in cooperation with a human operator. For example, vehicles maybe capable of various levels of autonomous control or may have more orless sophisticated implementations of a certain level of autonomouscontrol (e.g., quality of the vehicle's road sensors and processingabilities to determine a best or safest course of action in response toa road hazard). Another way vehicles differ from one another is thenotifications that the vehicle is capable of displaying to the humanoperator in the event of a change to the autonomous capabilities of thevehicle. Some vehicles may display notifications that are not aseffective in attracting the attention of a human operator as othernotifications. Some vehicles may incorporate notification aspectsincluding haptic feedback, audio feedback, heads-up displays, screendisplays, etc. to increase the effectiveness of a notification on thehuman driver. Some vehicle are capable of choosing a more intrusive orless intrusive type of notification depending on which is moreappropriate in view of a potential road hazard. Vehicles equipped withthese capabilities may be less likely to incur a loss that othervehicles that lack the capabilities when traveling with human operatorsof the same driving capability.

FIG. 2 is a time-series schematic diagram of an example system 200 forassessing driver ability to operate an autonomous vehicle. The twodrivers are designated in FIG. 2 as Driver A and Driver B. Drivers A andB are shown in a time progression from time T₁ to time T₅ in the processof engaging manual control of their respective vehicles. Both of thevehicles of Drivers A and B are vehicles that have some level ofautonomous capabilities and may be shifted up or down among levels ofautonomous capability to add or remove autonomous competencies to theset of autonomous capabilities exercised by the vehicle at a point intime.

At a time T₁, the vehicles of Drivers A and B receive a request toengage manual control in their respective vehicles. The request toengage manual control may originate from a security arbiter on thevehicles that makes autonomous capability decisions based on humanoperator parameters detected from observing the human operators (e.g.,Driver A and Driver B) in the vehicles, road condition data (e.g.,relayed from other vehicles, received from a monitoring party, based onlocal vehicle diagnostic data, etc.), and/or data regarding the humanoperators themselves (e.g., driving history, demographic data, insurancecoverage data, etc.). In another implementation, the request to engagemanual control may originate from another party with an interest in thevehicle and/or the occupants therein (e.g., a vehicle owner, a vehiclemanufacturer, an insurer, a law enforcement or other government agency,etc.). Also at time T₁, the vehicles of Drivers A and B display anotification requesting to engage manual control to the human operatorsof the vehicles. The notification may be displayed by a notificationserver on the vehicle that displays a notification as specified by asecurity arbiter on the vehicle.

At a time T₂, Driver A engages manual control. Various metrics may beused to determine when a human operator has successfully completed anengagement of manual control. Some metrics may be human operatorparameters sensed or detected by the vehicle. For example, a cameradisposed inside the vehicle may focus on a human operator's eyes and eyemovements to determine whether the human operator's attention is focuseson road conditions and the environment surrounding the vehicle or if thehuman operator's attention is focused on objects inside the vehicle. Ahuman operator's eye movements may also indicate whether the humanoperator is frequently checking mirrors (e.g., rear-view mirror, sidemirrors) and whether the eye movement patterns match known patterns ofattentive driving. Successful completion of manual control engagementmay also be detected by interactions of the human operator with thecontrols of the vehicle (e.g., operating the pedals, moving the steeringwheel, shifting gears, etc.).

At a time T₃, Driver A has engaged manual control but Driver B has not.In one implementation, the vehicle displays a continued request formanual control engagement of Driver B. The continued request for manualcontrol engagement of Driver B may include more or different elementssuch as lights, haptic feedback, a text message, sound instructions oralarms, etc. At a time T₄, Driver B engages manual control, and at timeT₅, when the vehicles reach the road hazard, both are under manualcontrol.

As illustrated in the example of FIG. 2 , different individual humanoperators respond differently to notifications to engage manual controlof a vehicle (or to change a level of autonomous capability of avehicle). In at least one implementation, Driver A and Driver B bothexhibit detected human operator parameters (level of engagement inanother activity, health status, etc.) that indicate a similar level ofalertness. Nevertheless, the two drivers respond differently to anotification to increase driving responsibility and take a differentamount of time before they are able to engage manual control of thevehicle (from T₁-T₂ for Driver A in comparison to T₁-T₄ for Driver B).These differences in reaction time may be recorded in a driving abilityprofile of each of the two drivers and included in the human operatorparameters relied upon to determine when to transition control of thevehicle, what types of alerts to use to notify the human operators of animpending change in driving responsibility, and how long the humanoperators are expected to need to successfully engage manual control.

FIG. 3 is a plot 300 of likelihood of loss against driving capabilityprofile in an example system for accessing driver ability to operate anautonomous vehicle. The x-axis of plot 300 indicates a rising drivingcapability profile and the y-axis of plot 300 indicates a likelihood ofloss. As driving capability profile increases along the x-axis, thelikelihood of loss to the vehicle being operated by the human operatorfalls. The plot 300 may also depend on factors including anenvironmental profile of the vehicle and/or human operator parameters ofthe human operator at a certain point in time. In other words, a humanoperator's driving capability profile, and thus the plot 300corresponding to the particular human operator, may shift depending onwhether the human operator's alertness level and skill in navigating theenvironment in which the vehicle is located at a certain point in time(e.g., an alert driver who is nervous about driving in a snowstorm mayscore differently than a distracted driver who is very experienced insnow driving conditions).

FIG. 4 is a schematic diagram 400 of road hazards 412 on a road 406carrying autonomously navigated vehicles. Under some circumstances, itmay be safer for a vehicle on road 406 to alter available autonomouscapabilities to more safely navigate the road hazards 412. To make adetermination whether it is safer to alter autonomous vehiclecapabilities or to remain in the status quo, the vehicle detects avariety of human operator parameters regarding a human operator of thevehicle to determine a human operator alertness level. An amount of timeneeded to alert a human operator of a vehicle to increase drivingresponsibilities regarding navigation of road hazards 412 depends inpart on the driving capability profiles of the various human operatorsof the vehicles on road 406. Also relevant to a determination of whetherit is safer to alter autonomous vehicle capabilities of the vehicle onroad 406 is an assessment of conditions on the road 406 and of the roadhazards 412.

The vehicles on road 406 include components for managing a transitionfrom one level of autonomous capabilities to another level of autonomouscapabilities. One type of component to manage the transition is anevaluator in the vehicles to evaluator to evaluate readiness of a humanoperator of a vehicle including one or more sensors. A security arbiterin the vehicles determines a security risk to the vehicle (e.g., a roadhazard, adverse conditions, diminished capacity of a human operator,etc.) and determines whether a level of autonomous capability of thevehicle should be adjusted by adding or removing autonomous capabilitiesand conversely adding or removing driving responsibility from a humanoperator. The security arbiter in the vehicle may receive human inputparameters directly from the human operator and/or from a remote party.

In at least one implementation, the security arbiter in the vehiclesevaluates a threat posed by the road hazards 412. The security arbitermay receive information regarding the threat from other roadparticipants and remote parties. For example, vehicles closer to theroad hazards 412 may wirelessly relay information back to other vehiclesfurther from road hazards 412 and the other vehicles approaching theroad hazards 412 on the other side of road 406 from the hazards. Thesecurity arbiter may receive indications, for example without limitationthat the vehicles have encountered sharply lower road speeds or haveobserved adverse road conditions. The vehicles may further relayinformation regarding the location of the road hazards 412 on the road406. The vehicles may include telematics data in the information sent tothe security arbiter (e.g., heavy braking, high G-forces, etc.). Asanother example, third parties (e.g., government agencies, insurers,vehicle owners, etc.) may collect information regarding the conditionson the road 406 by way of remote sensors. The remote sensors may detectroad speeds and be able to determine whether vehicles are in distress orif a dangerous condition has developed on the road 406. Remote sensorsmay be fixed in place roadside (e.g., vibration sensor, vehicle counter,camera, etc.) or may be mobile sensors (e.g., drone, unmanned aerialvehicle, helicopter, etc.).

After receiving data regarding the road hazards 412, the securityarbiter may determine a security threat to the vehicle based on the roadhazard 412 and other information available to the security arbiter. Thesecurity arbiter may further determine a change to autonomous vehiclecapabilities that should be taken to improve safety when navigating theroad hazard 412. Such a determination may be based on informationavailable to the security arbiter or it may be an instruction receivedfrom a third party. The security arbiter may further determine a timeperiod during which the change in the vehicle's autonomous capabilityshould occur.

Another component in the vehicles is a notification server. Thenotification server in the vehicles may include hardware and softwarecomponents (e.g., a display for text messages to a human operator insidethe vehicle, speakers for playing audio text notifications andinstructions, lights, feedback devices, an operating system,microphones, etc.) for presenting information to and receivinginformation from a human operator of the vehicles. The notificationspresented to a human operator of the vehicles on road 406 depends inpart on the driving capability profiles of the human operators of thevarious vehicles. A driver with a better driving capability profile forthe conditions present on road 406 may need less time to react to anotification than a driver with a poorer driver capability profile forthe conditions present on road 406. The notification server maytherefore select a longer notification period time for the respectivedrivers based on the driving capability profile.

After receiving data regarding the road hazard 412, the security arbitermay select a time period during which the vehicle should transition to adifferent level of autonomous capability. The time period may becalibrated based on the speed of the vehicles on the road 406, thelocation of the road hazards 412, information received from vehicles,etc. In at least one implementation, the security arbiter may decreasespeed of the vehicle to lengthen the time until the vehicle reaches theroad hazard 412. In at least one implementation, the security arbiterprovides a time period to the notification server of the vehicle duringwhich changes to the vehicle's autonomous capabilities should be made.In implementations, a security arbiter requests the notification serverto require human operator acknowledgement before implementing changes tothe autonomous capabilities of the vehicle. In another implementation,the security arbiter will cease navigation of the vehicle if the humanoperator does not acknowledge increased driving responsibilities. Inother implementations, the security arbiter implements a change in theautonomous capabilities of the vehicle.

FIG. 5 is an in-vehicle view of an example system 500 for assessingdriver ability to react to road conditions and/or accept additionaldriving responsibilities. In the implementation illustrated in FIG. 5 ,a text notification 502 appears on the dashboard of the vehicle. In oneimplementation, the text notification 502 alerts a human operator of animpending change to the level of autonomous control exercised by thevehicle or (as illustrated in FIG. 5 ) simply a notification to increaseawareness of road conditions in preparation for a potential change toautonomous capabilities. For example, if the vehicle or another entityhas determined that a greater degree of autonomous control is bettersuited to the potential road hazard, then the text notification 502 mayindicate to the human operator that the vehicle will include greaterautonomous capability (and thus less human responsibility) to navigatethe upcoming road hazard. The text notification 502 may includeinformation regarding the road hazard or an impending shift ofautonomous vehicle capabilities (e.g., whether the human operator isexpected to exercise a greater or lesser degree of control, the urgencyof the hazard or shift in capabilities, an expected time until thehazard is encountered or the shift in capabilities is executed, etc.).

In the case of a notification 502 that merely requests an increasedlevel of awareness on the part of the human operator, such anotification may provide a “head start” on the process of transitioningsome or all control from the vehicle to the human operator. In at leastone implementation, the notification 502 is one of a cascade ofnotifications ranging from merely requesting increased awareness totransfer of full control to the human operator, with intermediatenotifications for transfer of discrete autonomous capabilities to thehuman operator (e.g., braking but not steering, acceleration,deceleration, lane keeping, signaling, navigating, etc.). In anotherimplementation, the notification 502 in accompanied by other changes tothe environment inside the vehicle to assist the human operator inincreasing awareness of the road conditions surrounding the vehicle(e.g., turning down music, interrupting video display, etc.).

The text notification 502 may be adjusted to be more intrusive or lessintrusive to the human operator, depending on the nature of the roadhazard or change in autonomous capabilities. If the vehicle is preparingto gain more control over navigation of the vehicle with a correspondingreduction in responsibility on the part of the human operator, then thenotification 502 need not be highly intrusive because the notification502 is more of an informational nature. On the other hand, if there is aproblem with the vehicle's autonomous capabilities and the humanoperator is expected to take some or all responsibility for piloting thevehicle, then the notification 502 may be more intrusive to the humanoperator because the human operator must be made aware of the alert,which could involve interrupting another activity that the humanoperator may be engaged in (e.g., sleeping, reading, working, inconversation with another occupant of the vehicle, etc.). The textnotification 502 may be made more or less intrusive to the humanoperator by changing text font, flashing text, increasing or decreasingbrightness of the text notification 502, using colors to indicateurgency (e.g., red for high urgency, yellow or intermediate urgency,green for lower urgency, etc.).

In the implementation illustrated in FIG. 5 , haptic feedback 504 may beused to notify a human operator of an impending road hazard or change inautonomous vehicle capabilities. Haptic feedback may emanate from hapticdevices embedded in various parts of the interior of the vehicle such asin the vehicle seats, arm rests, headrests, vehicle and/or media controlsurfaces, etc. Haptic feedback signals 504 may accompany a textnotification 504. Haptic feedback signals 504 may be used to make anotification more intrusive to a human operator. For example, if a humanoperator is deemed to be in a state of lowered attention span, such aswhen sleeping, reading a book, etc., then a haptic feedback signal 504may assist in helping the human operator to “snap out” of her currentstate and to re-focus on the notification 502 and/or any road or vehicleconditions that require her attention.

Additionally, or alternatively, an audio alert 506 may be used to notifya human operator of an impending road hazard, an impending change inautonomous vehicle capabilities, or simply (as illustrated in FIG. 5 ) anotification to increase road awareness in the event that a change inautonomous driving capability is needed. An audio alert 506 may emanatefrom speakers located around the interior of the vehicle. Audio alert506 may include sounds designed to attract the attention of a humanoperator and/or voice commands directed to the human operator. Forexample, a voice command in the audio alert 506 may instruct the humanoperator to prepare for an increase in driving responsibility or signalto the human operator how much time is left until the human operatorwill be expected to exercise more or less control over the vehicle. Theaudio alert 506 may be made more intrusive or less intrusive to a humanoperator by varying the volume of the audio alert 506, including a soundreflective of the urgency of impending changes to the human operator'sresponsibilities (e.g., an alarm sound for an urgent hazard, a softvoice or bell for a less urgent hazard, etc.).

In at least one implementation, the audio alert 506 includes a “keyword”that the human operator has been conditioned to respond to. For example,the human operator's name may be used as a signal to attract the humanoperator's attention. In another limitation, the keyword may be awarning word (e.g. “danger,” “look out,” “alert!”) that the humanoperator may be conditioned to respond to. When the human operator hearsthe keyword, she is more likely to shift her attention away from othertasks and to focus on the road conditions surrounding the vehicle. Akeyword may be more effective than a beep, bell, or other signal thatthe human operator is less likely to have been conditioned to respondto.

In at least one implementation, other visual alerts 508 are included tonotify a human operator of an impending road hazard or impending changein autonomous vehicle capabilities. In one implementation, the visualalerts 508 include a light bulb (e.g., a light emitting diode) forflashing or steady illumination. In other implementations, the visualalerts 508 include an e-fabric display of images or colors on theinterior of the vehicle (e.g., an alert symbol, a text message, a colorindicating urgency, etc.). Like other alerting mechanisms in thevehicle, the visual alert 508 may be adjusted to be more intrusive orless intrusive to the human operation by varying the intensity of thealert (e.g., brightness of a light bulb), flashing the visual alert 508,changing the color of the visual alert 508, changing a message or symboldisplayed by the visual alert 508, etc.

FIG. 6 is an in-vehicle view of an example system 600 for assessingdriver ability to react to road conditions and/or accept additionaldriving responsibilities. The system 600 includes a text notification602 including request for acknowledgement from the human operator. Thetext notification 602 may serve as a “ping” to the human operator totest for responsiveness. When a human operator responds to the textnotification 602 (e.g., through a touch interface, pushing a button,speaking a response into a microphone, etc.), the system 600 (e.g., asecurity arbiter on the vehicle) may record a responsiveness timeassociated with the human operator's acknowledgement of the textnotification 602.

An intrusiveness level of the text notification 602 may be varied totest the human operator's reaction to different levels of intrusiveness.Some human operators may react well to minimally intrusive notificationsand find more intrusive notifications to be irritating. Other humanoperators, on the other hand, may not respond well to minimallyintrusive notifications and may need more intrusive notifications torespond to a request by the vehicle to assume more drivingresponsibility.

The push notification 602 includes an instruction for the human operatorto push and/or otherwise interact with the notification 602 to confirman alertness level of the human operator. The human operator'sinteraction with the notification 602 may serve as an acknowledgement ofthe request. The human operator's acknowledgement of the notification602 may be used to adjust a driving capability profile of the humanoperator. For example, if the human operator exhibits human operatorparameters that indicate the human operator is alert and focused on theenvironment surrounding the vehicle, then the driving capability profilefor that human operator may be adjusted to reflect that the humanoperator tends to respond quickly to notifications if the human operatoris alert and focused on the surroundings of the vehicle. On the otherhand, if the human operator is focused on another activity, such asreading book, then the human operator's response to the notification 602may be much slower, and the driving capability profile of the humanoperator may be adjusted to reflect that the particular human operatorresponds slowly if the human operator parameters indicate that the humanoperator is focused on reading a book. Still other human operators maystill respond quickly to the notification 602 when engrossed in readinga book, and the driving capability profiles of these human operators areadjusted to reflect their faster response time even though they may befocused on an activity other than monitoring the environment surroundingthe vehicle.

FIG. 7 is an in-vehicle view of an example system 700 for assessingdriver ability to react to road conditions and/or accept additionaldriving responsibilities. The system 700 includes a text display 702 foralerting a human operator of an impending change to autonomous vehiclecapabilities of the vehicle. In the implementation illustrated in FIG. 7, the vehicle or another party has determined that an expected roadhazard should not be navigated by the vehicle autonomously. Some roadhazards (e.g., a rock slide) are very serious and seldom encountered byautonomous vehicle. It may not be known how well an autonomous vehicleis able to navigate such a hazard due to unpredictable conditions andinfrequent collection of the behavior of autonomous vehicle in such asituation. In such cases, it may be determined that a human operatormust quickly assume control of the vehicle.

The determination that an expected road hazard should not be navigatedautonomously may be based on information collected by the vehicle itselfor may be reported to the vehicle via a communications interface (e.g.,other vehicles in the area may send reports that they are notsuccessfully navigating a road hazard, an insurer may determine thathuman operators in general or a human operator in particular is morelikely to safely navigate a road hazard than a vehicle under autonomouscontrol, etc.). The text notification 702 may be accompanied by othernotification methods (e.g., audio signal, haptic feedback, visualsignals, etc.). The text notification 702 may further includeinformation such as an expected amount of time until a road hazard willbe reached or an expected amount of time until a change to autonomousdriving capabilities takes effect. The human operator's response to thetext notification 702 may be used to adjust a driving capability profileof the human operator depending on the human operator's response time,human operator parameters at the time of the text notification 702,environmental conditions of the vehicle at the time of the textnotification 702, etc.

FIG. 8 is a schematic diagram of an example system 800 for assessingdriver 810 ability to operate an autonomous vehicle 802. The system 800includes a vehicle 802 with more than one level of autonomouscapabilities navigating on a road 804. The vehicle 802 may include onelevel of pure manual control and one or more additional levels ofenhanced automated control. When the vehicle 802 approaches a potentialroad hazard 806 or other road conditions under which a change in theautonomous capabilities of the vehicle 802 are warranted, the vehicle802 may display a notification to the human operator 810 to expect anupcoming or immediate change in the responsibilities of the humanoperator 810 in piloting the vehicle 802.

One factor in determining the type of notification of a change inautonomous capabilities of the vehicle 802 to the human operator 810 isthe current state of the human operator 810. An alertness level of thehuman operator 810 may be estimated based on objective data collected bysensors inside the vehicle 802 such as the sensors shown in the bubble808 of the interior of the vehicle 802. In one implementation, anoptical imaging device 812 (e.g., a camera) is located inside thevehicle 802 and is directed towards the human operator 810. The camera812 may capture images of the human operator 810 that may be analyzed toextract human operator parameters used to determine an alertness stateof the human operator.

In at least one implementation, the human operator parameters include abody position of the human operator 810. If the human operator 810 issitting upright in the seat 814 and has her hands on or near a steeringwheel, it is likely that the human operator 810 will be more responsiveto a change in driving responsibilities than if the human operator 810is reclined in the seat 814 without hands near the steering wheel.Images captured by the camera 812 may be analyzed by components of thevehicle 802 to determine whether the human operator is in a bodyposition that indicates a greater or lower level of alertness. Thecamera 812 may capture a series of images of the human operator 810(e.g., a video) that may be compared by components of the vehicle 802 todetermine an activity level of the human operator 810. For instance, ifthe human operator 810 is asleep, then she will likely exhibit adifferent movement patterns than a human operator 810 who is awake.Another type of objective data that may be collected by the camera 812regarding the human operator's alertness and preparedness for acceptinga change in driving responsibilities is the activity in which the driveris engaged. If analysis of images captured by the camera 812 indicatethat the human operator 810 is holding a book or electronic device, forexample, then the human operator 810 is more likely to experience aslower change of focus away from the book and to road conditions than ahuman operator 810 who is not holding a book or electronic device. Thecamera 812 may also capture images of the face of the human operator 810to determine whether her eyes are open or closed, focused on theenvironment outside of the vehicle 802 or inside the vehicle 802 andother factors such as fatigue.

FIG. 9 is a schematic diagram of an example system 900 for assessingdriver ability to operate an autonomous vehicle. The vehicle 906includes an image capture device 904 such as a camera. The camera may bedirected towards the face of the human operator 902 and images capturedthereof. Components of the vehicle 906 may analyze the images of theface of the human operator 902 to identify characteristics of the humanoperator 902 that are relevant to the human operator parameters used todetermine an alertness level of the human operator 902.

The camera 904 may analyze various features of the human operator 902 tosupply human operator parameters to the vehicle 906. For example, in atime period before time 910, the eyes of the human operator 902 are openand focused outside the window of the vehicle 906. The camera 904 maycapture a series of images of the face of the human operator 902 todetect other features such as rapidity of eye movement, dilation of eyepupils, blinking, etc.

In a time period after time 910, the camera may capture more images ofthe face of the human operator 902. In a time period after time period910, the eyes of the human operator 902 are still open, but are focusedon a book 914. Images captured by the camera 904 may reflect that theeyes of the human operator 902 are no longer focused on the environmentsurrounding the vehicle 906, but instead are focused on the book 914.Images captured by the camera 904 may record features of the eyes of thehuman operator 902 such as eye movements indicating a speed at which thehuman operator 902 is reading. Slower reading speeds and other eyemovements may indicate a fatigue level of the human operator 902.

If the eyes of the human operator 902 are no longer focused on theenvironment surrounding the vehicle, human operator parameters mayinclude a level of distraction represented by a “score.” For example, ifthe human operator 902 is focused on a book 914, it may be likely thatthe human operator is engaging in an extended period of perhaps intenseconcentration on the book 914. The longer the human operator 902 focuseson the book 914, the more likely she is to have a higher level ofdetachment from her environment. Such behavior may indicate that thehuman operator parameters should reflect a higher level of distraction.A security arbiter in the vehicle 906 may set a relatively longer periodof time that would be expected before the human operator 902 responds toa notification of change to driving responsibility based on a higherdistraction score in the human operator parameters. On the other hand,if the human operator 902 is only occasionally focusing on a handhelddevice (e.g., checking email, etc.), then the distraction of the humanoperator 902, while still present, may not be considered as distractedas long periods of reading a book 914. In such a case, a lowerenvironmental detachment score may be included in the human inputparameters and relied on by other components of the vehicle 906 to alertthe human operator 902 of an impending change in driving responsibilityand management of shifting the vehicle from one level of autonomouscontrol to another.

At a time period after time 912, the camera 904 may capture additionalimages of the face of the human operator 902 that indicate the humanoperator 902 is suffering from fatigue. Images captured by the camera904 may show that that eye lids of the human operator 902 are not asopen as before the human operator 902 began experiencing fatigue. Othereye-based indications include blinking rate, location of eye focus, andeye movement rapidity.

The human operator parameters collected by the camera 904 are used todetermine an alertness level of the human operator 902. The determinedalertness level may be used to determine whether a change should be madeto the autonomous capability level of the 906 and whether the humanoperator 902 should take on more or less driving responsibility. If thevehicle 906 determines that an approaching road hazard 908 exists andthe human operator 902 should take on more driving responsibility, thenthe vehicle 906 may display a notification to the human operator 902.The type of notification displayed to the human operator 902 and thetime period for which the notification should be displayed in advance ofan encounter with the road hazard 908 depend on the alertness level ofthe human operator 902 and the human operator parameters sensed bycomponents of the vehicle 906. For example, if the human operator 902has a higher alertness level, such as in the time period before time910, then the notification of a change to the vehicle's autonomouscapabilities may be less intrusive or occur closer to a road hazardbecause it is expected that the human operator 902 will be able torecognize the notification and increase driving responsibilityrelatively quickly. On the other hand, if an alertness of the humanoperator 902 is lower due to human operator parameters such as thoseexamples after time 910 and after time 912 (e.g., occupied with anothertask, experiencing fatigue, etc.), then the notification of a change tothe vehicle's autonomous capabilities may be more intrusive or occurfarther away from the road hazard because it is expected that the humanoperator 902 will need relatively more time to recognize thenotification and prepare to increase driving responsibility.

FIG. 10 is an in-vehicle view of an example system 1000 for assessingdriver ability to react to road conditions and/or accept additionaldriving responsibilities. In the implementation illustrated in FIG. 10 ,a notification 1002 includes a request to the human operator to adjustthe level of autonomous control exercised by the vehicle. In somesituations, the vehicle may determine or a third party may determine,that a vehicle is likely to be navigated more safely autonomously thanby the human operator. Examples of third party entities that may makesuch a determination include a vehicle manufacturer, a governmentagency, an insurer, a vehicle owner, etc. The vehicle or the thirdparties may also determine that a vehicle is likely to be operated moresafely manually than autonomously in certain situations. In the exampleillustrated in FIG. 10 , an extreme weather alert issued from a weatherservice initiates a request to the human operator to agree to allow thevehicle reduce or eliminate autonomous capabilities in favor of manualcontrol. A human operator may interact with the notification 1002directly or by other controls in the interior of the vehicle to acceptthe request presented in notification 1002.

The display of notification 1002 may be conditioned on a drivingcapability profile of the human operator of the vehicle in comparison tohuman operator parameters detected by the vehicle and/or theenvironmental risk profile of the vehicle. For example, if the drivingcapability profile of a human operator of the vehicle indicates that thedriver has a poor level of skill in extreme weather conditions, then thearbiter may determine that it is safer if the vehicle navigates theextreme weather autonomously rather than under manual control of thehuman operator.

FIG. 11 is an in-vehicle view of an example system 1100 for assessingdriver ability to react to road conditions and/or accept additionaldriving responsibilities. In at least one implementation, an insurerdetermines whether a human operator or a vehicle is more likely tosafely navigate the vehicle in certain conditions. The insurer initiatesa request to the human operator to be displayed as notification 1102.The notification 1102 may include an offer from an insurer to lowerinsurance premium prices in return for the human operator's agreement toallow the vehicle to assume a greater or lesser degree of autonomouscontrol over road navigation depending on the rules preferred by theinsurer. Rules preferred by the insurer may depend on factors such asthe human operator parameters measured inside the vehicle, the drivingcapability profile of the particular human operator in the vehicle, anddata gathered regarding events outside the vehicle.

In one implementation, the notification 1102 is an in-vehiclenotification requesting adjustment based on factors such as the humanoperator's driving capability profile, human operator parameters, andpotential road hazards. The in-vehicle notification 1102 may thereforebe an on-demand change to the vehicle's autonomous capabilities based onchanging conditions. In another implementation, the notification 1102 isnot an in-vehicle notification, and may be based on an analysis of thehuman operator's driving capability profile and other informationrelating to the driver. In yet another implementation, the notification1102 indicates that current insurance coverage no longer covers thevehicle in case of a crash due to an increased risk as determined basedon current human operator parameters, driving capability profile, and/orroad conditions. If current insurance no longer covers the humanoperator, the notification 1102 may display an offer for the humanoperator to make a one-time (or recurring) additional premium payment tocontinue insurance coverage. In at least one implementation, the vehiclemay cease navigation if the human operator no longer has insurancecoverage and declines to pay an additional premium to continue coverage.In another implementation, the additional premium payment may bevariable based on a level of autonomous capability of the vehicle agreedto by the human operator.

FIG. 12 is an in-vehicle view of an example system 1200 for assessingdriver ability to react to road conditions and/or accept additionaldriving responsibilities. The system 1200 includes a text notification1202 indicating that the human operator qualifies for a reducedinsurance premium cost due to an improved driving capability profile. Ifhuman operators are aware that there is a driving capability profiledescribing their driving skills in various situations and that aninsurer may rely on the driving capability profile to set insurancepremium costs, especially for insuring an autonomous vehicle, then thehuman operators may attempt to increase their skill level reflected intheir driving capability profiles.

FIG. 13 illustrates example operations 1300 for assessing driver abilityto operate an autonomous vehicle. An identifying operation 1302identifies a human operator of a vehicle wherein the human operator hasa driving capability profile. The human operator's driving capabilityprofile may be based on multiple factors including without limitationthe results of a skill test of the human operator, a history of thehuman operator's prior responses to notifications of a change of achange to the vehicle's autonomous capabilities (especially responsetime and quality to notifications that the human operator should assumea greater degree of driving responsibility), typical usage patterns andlocations of the human operator, an insurance coverage amount of thevehicle, etc. In one implementation, the identifying operation 1302includes identifying the human operator via sensors inside the vehicle(e.g., a camera with facial recognition of the human operator).

A determining operation 1304 determines human operator parametersassociated with the human operator. The determining operation 1304 mayinclude sensors inside the vehicle to collect biometric data regardingthe human operator (e.g., camera, heart rate sensor, perspirationsensor, steering wheel grip force sensor, body temperature sensor,movement sensors, microphones, etc.). The determining operation 1304 mayalso rely on information about the human operator stored by the vehicleor communicated to the vehicle such as demographic information regardingthe human operator (age, gender, length of driving experience, etc.) andhistorical information regarding the human operator's usage of thevehicle.

A determining operation 1306 determines an environmental profile of anenvironment of the vehicle. The environmental profile may be based on anumber of available factors including information received from othervehicles operating on the same road (e.g., vehicle crash information,road hazard information, emergency control reports, traffic densityinformation regarding the road, etc.), information received from anentity monitoring the road (e.g., a government agency, insurer, etc.),and/or information detected by the vehicle itself (e.g., outside weatherand temperature conditions, traffic density, etc.). In oneimplementation, the environmental risk profile includes whether and howmany other vehicles on the same road are able to communicate with oneanother, especially whether the other vehicles on the road are able tocommunicate emergency signals to other vehicles and to respond toemergency signals received from other vehicles. If a significant portionof the vehicles travelling on a road together are able to shareemergency information with one another, then there is a reducedlikelihood of a vehicle crash and subsequent liability for an insurer.Also liability could be reduced where all vehicles respond similarly toa road hazard (e.g., when applying a legal standard of reasonableprecautions).

Another determining operation 1308 determines an alertness level of thehuman operator based on the human operator parameters and the drivingcapability profile. The determining operation 1308 may include adetermination of an amount of time the human operator is likely to needto respond to notifications of various levels of intrusiveness.

A signaling operation 1310 signals to the human operator with a signalrequesting a response from the human operator. In at least oneimplementation, the signal is a text notification displaying a messageto the human operator in the interior of the vehicle. In otherimplementations, the signal includes haptic feedback, video, audio,and/or other types of signaling. An updating operation 1312 updates adriving capability profile based on a response from the human operatorto the signaling operation 1310. The updating operation 1312 may dependat least in part on the environmental profile and the human operatorparameters at the time of the signaling operation 1310 to update thedriving capability profile. For example, if the human operator exhibitshuman operator parameters that indicate the human operator is notfocused on the conditions surrounding the vehicle, then any response tothe signaling operation 1310 will reflect the human operator'spropensity and level of skill in switching focus from the object of thehuman operator's attention (e.g., electronic device, book, etc.) to theroad and preparations for potentially taking control of the vehicle.

FIG. 14 illustrates example operations 1400 assessing driver ability tooperate an autonomous vehicle. A receiving operation 1402 receives adriving capability profile of a human operator of a vehicle. The drivingcapability profile of the human operator may be stored on-board avehicle or it may be transmitted from a third party (e.g., a governmentagency, a driver assessment entity, an insurer, etc.). A receivingoperation 1404 receives an environmental profile of a vehicle. Theenvironmental profile may be based on a number of available factorsincluding information received from other vehicles operating on the sameroad (e.g., vehicle crash information, road hazard information,emergency control reports, traffic density information regarding theroad, etc.), information received from an entity monitoring the road(e.g., a government agency, insurer, etc.), and/or information detectedby the vehicle itself (e.g., outside weather and temperature conditions,traffic density, etc.). In one implementation, the environmental riskprofile includes whether and how many other vehicles on the same roadare able to communicate with one another, especially whether the othervehicles on the road are able to communicate emergency signals to othervehicles and to respond to emergency signals received from othervehicles. If a significant portion of the vehicles travelling on a roadtogether are able to share emergency information with one another, thenthere is a reduced likelihood of a vehicle crash and subsequentliability for an insurer. Also liability could be reduced where allvehicles respond similarly to a road hazard (e.g., when applying a legalstandard of reasonable precautions).

A determining operation 1406 determines a risk of insuring the vehicle,the risk being based at least in part on the driving capability profileand the environmental profile. The risk of insuring the vehicle may beextended to various periods of time. For example, if the combination ofthe driving capability profile and the environmental risk profileindicates that the human operator will fare poorly in expected snow roadconditions, but that the snow road conditions will only persist for ashort time until the vehicle reaches its destination, then the risk ofinsuring the vehicle may extend only for the duration of the trip. Onthe other hand, the risk of insuring the vehicle may extend indefinitelyand may be based on the driving capability profile and a historicalassessment of all environmental profiles the vehicle is likely toencounter while being used by the human operator. The determiningoperation may further be based on human operator parameters detectedduring the operations 1400. For example, if human operator parametersindicate that the human operator is experiencing a level of intoxicationthat is likely to impair the human operator's driving capabilitiescompared to the human operator's non-intoxicated driving capabilities,then the determining operation 1406 may extend only to a period of timewhen the human operator is expected to remain intoxicated.

A transmitting operation 1408 transmits an insurance offer to the humanoperator or to another entity with an interest in the vehicle, theinsurance offer being based at least in part on the determiningoperation 1406. The insurance offer may extend only to a time periodduring which the determining operation 1406 is valid (e.g., for as longas the risk is expected to remain at the level determined by thedetermining operation 1406).

Of course, the applications and benefits of the systems, methods andtechniques described herein are not limited to only the above examples.Many other applications and benefits are possible by using the systems,methods and techniques described herein.

Furthermore, when implemented, any of the methods and techniquesdescribed herein or portions thereof may be performed by executingsoftware stored in one or more non-transitory, tangible, computerreadable storage media or memories such as magnetic disks, laser disks,optical discs, semiconductor memories, biological memories, other memorydevices, or other storage media, in a RAM or ROM of a computer orprocessor, etc.

The patent claims at the end of this patent application are not intendedto be construed under 35 U.S.C. § 112(f) unless traditionalmeans-plus-function language is expressly recited, such as “means for”or “step for” language being explicitly recited in the claim(s). Thesystems and methods described herein are directed to an improvement tocomputer functionality, and improve the functioning of conventionalcomputers.

What is claimed:
 1. A method of assessing driver capability for operating an autonomous vehicle, the method comprising: identifying, by one or more processors, a human operator of the autonomous vehicle, the human operator being associated with a driving capability profile; signaling, by the one or more processors, to the human operator with a signal, the signal requesting a response from the human operator; and updating, by the one or more processors, based on the response from the human operator to the signal, the driving capability profile to indicate a level of skill of the human operator at responding to the signal.
 2. The method of claim 1, further comprising: determining, by the one or more processors prior to the signaling, human operator parameters associated with the human operator of the autonomous vehicle, wherein updating the driving capability profile is further based on the human operator parameters.
 3. The method of claim 2, wherein determining the human operator parameters includes: determining whether eyes of the human operator are focused on an object inside the autonomous vehicle.
 4. The method of claim 2, further comprising: determining, by the one or more processors, an alertness level of the human operator based on the human operator parameters, wherein updating the driving capability profile includes updating the driving capability profile to indicate the level of skill of the human operator at responding to the signal at the determined alertness level.
 5. The method of claim 1, wherein the signal is a first signal, the method further comprising: detecting, by the one or more processors, than an autonomous capability of the autonomous vehicle is to change; and in response to the detecting, signaling, by the one or more processors, based on the driving capability profile, to the human operator with a second signal.
 6. The method of claim 5, further comprising: determining, by the one or more processors, an alertness level of the human operator, wherein the signaling to the human operator with the second signal is further based on the alertness level.
 7. The method of claim 1, further comprising: determining, by the one or more processors, an environmental profile of the autonomous vehicle, the environmental profile reflecting conditions surrounding the autonomous vehicle, wherein updating the driving capability profile is further based on the environmental profile.
 8. The method of claim 7, wherein the environmental profile of the autonomous vehicle includes one or more of weather conditions or daylight conditions.
 9. The method of claim 1, wherein updating the driving capability profile to indicate the level of skill comprises: updating the driving capability profile to indicate an amount of time between the signaling operation and the response from the human operator.
 10. The method of claim 1, wherein updating the driving capability profile is further based on at least one of a type of response from the human operator or a type of signal used by the signaling operation.
 11. A computer system for assessing driver capability for operating an autonomous vehicle, the computer system comprising: one or more processors; a non-transitory computer-readable memory coupled to the one or more processors and storing instructions thereon that, when executed by the one or more processors, cause the computer system to: identify a human operator of the autonomous vehicle, the human operator being associated with a driving capability profile; signal to the human operator with a signal, the signal requesting a response from the human operator; and update, based on the response from the human operator to the signal, the driving capability profile to indicate a level of skill of the human operator at responding to the signal.
 12. The computer system of claim 11, wherein the instructions further cause the computer system to: determine, prior to the signaling, human operator parameters associated with the human operator of the autonomous vehicle, wherein updating the driving capability profile is further based on the human operator parameters.
 13. The computer system of claim 12, wherein the instructions cause the computer system to determine the human operator parameters by: determining whether eyes of the human operator are focused on an object inside the autonomous vehicle.
 14. The computer system of claim 12, wherein the instructions further cause the computer system to: determine an alertness level of the human operator based on the human operator parameters, wherein updating the driving capability profile includes updating the driving capability profile to indicate the level of skill of the human operator at responding to the signal at the determined alertness level.
 15. The computer system of claim 11, wherein the signal is a first signal, and the instructions further cause the computer system to: detect than an autonomous capability of the autonomous vehicle is to change; and in response to the detecting, signal, based on the driving capability profile, to the human operator with a second signal.
 16. The computer system of claim 15, wherein the instructions further cause the computer system to: determine an alertness level of the human operator, wherein the signaling to the human operator with the second signal is further based on the alertness level.
 17. The computer system of claim 11, wherein the instructions further cause the computer system to: determine an environmental profile of the autonomous vehicle, the environmental profile reflecting conditions surrounding the autonomous vehicle, wherein updating the driving capability profile is further based on the environmental profile.
 18. The computer system of claim 17, wherein the environmental profile of the autonomous vehicle includes one or more of weather conditions or daylight conditions.
 19. The computer system of claim 11, wherein the instructions cause the computer system to update the driving capability profile to indicate the level of skill by: updating the driving capability profile to indicate an amount of time between the signaling operation and the response from the human operator.
 20. A method of insuring an autonomous vehicle against loss, the method comprising: receiving, by one or more processors, a driving capability profile of a human operator of the autonomous vehicle; receiving, by the one or more processors, a response from the human operator to a signal, the signal presented to the human operator and requesting a response from the human operator; updating, by the one or more processors, based on the response from the human operator to the signal, the driving capability profile to indicate a level of skill of the human operator at responding to the signal; determining, by the one or more processors, a risk of insuring the autonomous vehicle, the risk being based at least in part on the updated driving capability profile; and transmitting, by the one or more processors, an insurance offer to an electronic device associated with the human operator, the insurance offer being based at least in part on the determined risk of insuring the autonomous vehicle. 